A pilot randomized controlled trial of a group intervention via Zoom to relieve loneliness and depressive symptoms among older persons during the COVID-19 outbreak
Bibliographic record
Abstract
While effective in reducing infections, social distancing during the COVID-19 outbreak may carry ill effects on the mental health of older adults. The present study explored the efficacy of a short-term digital group intervention aimed at providing seniors with the tools and skills necessary for improving their coping ability during these stressful times. A total of 82 community-dwelling adults aged between 65 aged 90 (Mage = 72 years, SD = 5.63) were randomized to either an intervention group (n = 64) or a wait-list control group (n = 18). The intervention comprised online guided sessions in small groups in which behavioral and cognitive techniques were learned and practiced via the ZOOM videoconferencing platform. Loneliness and depression levels were measured pre- and post-participation. The results demonstrated a significant improvement in the intervention group in terms of both loneliness and depressive symptoms, compared with the control group. Results of mixed effect models indicated a medium ameliorative effect on loneliness (d = 0.58), while that for depressive symptoms was only marginally significant and smaller in size (d = 0.43). Our intervention presents a relatively simple and effective technique that can be efficiently utilized to support older adults both during emergencies such as the COVID-19 outbreak, as well as in more routine times for older adults who live alone or reside in remote areas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".